
This document introduces the KAIA Research Series and provides an overview of the five papers that establish Geometric Context Modeling as a new field of artificial intelligence. It is intended for readers encountering this work for the first time, whether from research, industry, policy, or education backgrounds. The series was produced entirely through independent research conducted between April and May 2026, across 27 experiments, without institutional support, a research budget, or GPU hardware. It was conducted on standard consumer CPU hardware, which is itself a demonstration of the core claim: serious AI research does not require the resources that most people do not have.
word embeddings, Artificial intelligence, Artificial Intelligence/statistics & numerical data, Artificial Intelligence/ethics, semantic reasoning, Natural language processing, CPU-native AI, Artificial Intelligence/standards, agent architecture, AI equity, Artificial Intelligence, Artificial Intelligence/trends, geometric context modeling, Natural Language Processing
word embeddings, Artificial intelligence, Artificial Intelligence/statistics & numerical data, Artificial Intelligence/ethics, semantic reasoning, Natural language processing, CPU-native AI, Artificial Intelligence/standards, agent architecture, AI equity, Artificial Intelligence, Artificial Intelligence/trends, geometric context modeling, Natural Language Processing
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
